Beginner
Data Science with R: Data Analysis and Visualization

Data Science with R:
Data Analysis and Visualization

This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which you will learn the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

* Tuition paid for part-time courses can be applied to the Data Science Bootcamps if admitted within 9 months.
In response to COVID-19, all of our scheduled in-person professional development courses will be temporarily conducted remote/live online.

Course Dates

Earlybird ends on 12/10
January Session

Jan 9 - Feb 6, 2021
Saturday
10:00am-5:00pm

$2190.00
$2190.00
$2080.50
Enroll Now
Earlybird ends on 01/28
February Session

Feb 27 - Mar 27, 2021
Saturday
10:00am-5:00pm

$2190.00
$2190.00
$2080.50
Enroll Now
Find out more information about our professional development courses.
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Product Description

Course Overview

This course is a 35-hour program designed to provide a comprehensive introduction to R for Data Analysis and Visualization. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

Prerequisites

  • Basic knowledge about computer components
  • Basic knowledge about programming

Certificate

Certificates are awarded at the end of the program at the satisfactory completion of the course. Students are evaluated on a pass/fail basis for their performance on the required homework and final project (where applicable). Students who complete 80% of the homework and attend a minimum of 85% of all classes are eligible for the certificate of completion.

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Demo Lecture

Character Manipulation
Module
Basic Data Elements
Instructor
Jay Lee
Description
NYC Data Science Academy's Instructor, Jay Lee, walks through a lecture on regular expression in R.

Syllabus

Unit 1: Basic Programming with R

  • Introduction to R
    • What is R?
    • Why R?
    • How to learn R
    • RStudio, packages, and the workspace
  • Basic R language elements
    • Data object types
    • Local data import/export
    • Introducing functions and control statements
  • In-depth study of data objects
  • Functions
  • Functional Programming

Unit 2: Basic Data Elements

  • Data transformation
    • Reshape
    • Split
    • Combine
  • Character manipulation
  • String manipulation
  • Dates and timestamps
  • Web data capture
  • API data sources
  • Connecting to an external database

Unit 3: Manipulating Data with “dplyr”

  • Subset, transform, and reorder datasets
  • Join datasets
  • Groupwise operations on datasets

Unit 4: Data Graphics and Data Visualization

  • Core ideas of data graphics and data visualization
  • R graphics engines
    • Base
    • Grid
    • Lattice
    • ggplot2
  • Big data graphics with ggplot2

Unit 5: Advanced Visualization

  • Customized graphics with ggplot2
    • Titles
    • Coordinate systems
    • Scales
    • Themes
    • Axis labels
    • Legends
  • Other plotting cases
    • Violin Plots
    • Pie charts
    • Mosaic plots
    • Hierarchical tree diagrams
    • scatter plots with multidimensional data
    • Time-series visualizations
    • Maps
    • R and interactive visualizations

Our Alumni Feedback

This course was a masterpiece. Derek Darves the instructor, quickly brought us to competency with the R programming language. Then he expanded the course by introducing the packages used for analysis and visualization, progressing through introductory use to somewhat elegant and sophisticated programming challenges. Ultimately Derek brought us to a self-sufficiency level for continuing our R education. The course was a pleasure as Derek is clearly an R expert and aficionado weaving many practical tips and historical insights into the lectures. His programming experience, statistical insights and extensions of the course materials gave it a graduate level feel, while never ignoring the fundamental skills being taught. I highly recommend it.
Joe Keepers
This was a great introductory start to learn R due to the comprehensive syllabus and dedicated teacher effort. About the syllabus, you will learn Base R syntax and principal data structures identification and manipulation plus a bunch of other packages (e.g. DPLYR) that will make your life easier when treating data sets. The instructor was a Sr. Data Scientist that really gave us two sides: theoretical and hands-on day-to-day professional experience views. This was very helpful. I found that there're lots of courses out there but most of the times taught by recently-graduated teachers that haven't applied a lot of the syllabus to real-life professional situations. This for me was a plus. The only soft point of the course was that I would have liked to go more deeper into web scrapping, yet it's true this course name is 'data analysis and visualization in R' and not 'Web scrapping using R'. One advice only for prospect students: block your agendas during five weeks since you will need a lot of time to review the materials and deliver exercises, which after all it's not a bad thing as it makes you feel good as you feel you have learned a lot. Highly recommended.
Carlos S.
This was a great class that I truly enjoyed attending every Saturday for 5 weeks. The class had a pretty steep learning curve but the slides and the homeworks did a good job of teaching the material. Our instructor, Derek, was an R guru and could answer any question we threw at him. I definitely plan to continue learning R and I can attribute my enthusiasm to having taken this class.
Vinod Shekar
Great course to get started with R programming. Convenient location in the city, nice classroom mates with very different backgrounds, and an amazing instructor, Derek has an impressive deep knowledge of R and he is a very talented and dynamic teacher Totally recommended to gain beginner understanding of this language.
Sandra Barral
I really enjoyed the R course with instructor Amy Ma. The content is very practical. It can be directly applied to solve real-world data analysis problem. We had many in-class coding exercises, which helped us understand the R syntax. Also, Amy tried her best to provide a lot of useful resources. We could tell that she is very passionate about what she is doing, and she is patient with students. We could reach her after class through email, even the course was finished. I highly recommend this course to anyone who is interested in data analysis and wants to learn R from the beginning.
Jiaqi Luo

I completed the Intensive beginner course for R and I highly recommend it! I’ve learned a lot in 5 weeks and I can say that I am now an R convert (from SAS). I’ve learned so many functions and packages that I am now able to use them confidently at work. Vivian was also a great, hard working teacher who encouraged every one in the class to study harder which means she really cared that that her students would become great data scientists sooner than later. I like the class so much I am now taking the R intermediate class.

Marifel Corpuz
NYC Data Science Academy provided me great exposure to data science topics that I haven’t come across in either school or previous jobs. The hands-on assignments are practical and make use of real-world examples. As product development is becoming more data-driven, it will be crucial for product teams to have a solid grasp of data analysis which NYC Data Science Academy fills the knowledge/skill gap.
Donald Fleurantin
This course was a masterpiece. Derek Darves the instructor, quickly brought us to competency with the R programming language. Then he expanded the course by introducing the packages used for analysis and visualization, progressing through introductory use to somewhat elegant and sophisticated programming challenges. Ultimately Derek brought us to a self-sufficiency level for continuing our R education. The course was a pleasure as Derek is clearly an R expert and aficionado weaving many practical tips and historical insights into the lectures. His programming experience, statistical insights and extensions of the course materials gave it a graduate level feel, while never ignoring the fundamental skills being taught. I highly recommend it.
Joe Keepers
This was a great introductory start to learn R due to the comprehensive syllabus and dedicated teacher effort. About the syllabus, you will learn Base R syntax and principal data structures identification and manipulation plus a bunch of other packages (e.g. DPLYR) that will make your life easier when treating data sets. The instructor was a Sr. Data Scientist that really gave us two sides: theoretical and hands-on day-to-day professional experience views. This was very helpful. I found that there're lots of courses out there but most of the times taught by recently-graduated teachers that haven't applied a lot of the syllabus to real-life professional situations. This for me was a plus. The only soft point of the course was that I would have liked to go more deeper into web scrapping, yet it's true this course name is 'data analysis and visualization in R' and not 'Web scrapping using R'. One advice only for prospect students: block your agendas during five weeks since you will need a lot of time to review the materials and deliver exercises, which after all it's not a bad thing as it makes you feel good as you feel you have learned a lot. Highly recommended.
Carlos S.
This was a great class that I truly enjoyed attending every Saturday for 5 weeks. The class had a pretty steep learning curve but the slides and the homeworks did a good job of teaching the material. Our instructor, Derek, was an R guru and could answer any question we threw at him. I definitely plan to continue learning R and I can attribute my enthusiasm to having taken this class.
Vinod Shekar
Great course to get started with R programming. Convenient location in the city, nice classroom mates with very different backgrounds, and an amazing instructor, Derek has an impressive deep knowledge of R and he is a very talented and dynamic teacher Totally recommended to gain beginner understanding of this language.
Sandra Barral
I really enjoyed the R course with instructor Amy Ma. The content is very practical. It can be directly applied to solve real-world data analysis problem. We had many in-class coding exercises, which helped us understand the R syntax. Also, Amy tried her best to provide a lot of useful resources. We could tell that she is very passionate about what she is doing, and she is patient with students. We could reach her after class through email, even the course was finished. I highly recommend this course to anyone who is interested in data analysis and wants to learn R from the beginning.
Jiaqi Luo

I completed the Intensive beginner course for R and I highly recommend it! I’ve learned a lot in 5 weeks and I can say that I am now an R convert (from SAS). I’ve learned so many functions and packages that I am now able to use them confidently at work. Vivian was also a great, hard working teacher who encouraged every one in the class to study harder which means she really cared that that her students would become great data scientists sooner than later. I like the class so much I am now taking the R intermediate class.

Marifel Corpuz
NYC Data Science Academy provided me great exposure to data science topics that I haven’t come across in either school or previous jobs. The hands-on assignments are practical and make use of real-world examples. As product development is becoming more data-driven, it will be crucial for product teams to have a solid grasp of data analysis which NYC Data Science Academy fills the knowledge/skill gap.
Donald Fleurantin

Campus Location

500 8th Ave #905, New York, NY 10018
500 8th Ave Suite 905, New York, NY 10018
Nearby Subways
1 2 3 34th, Penn Station
A C E 34th, Penn Station
N Q R B D F M 34th, Herald Square

Instructors

Jay Lee
Jay Lee
Instructor
Jay Lee has been a life-long marketing expert specialized in quantitative analysis. He has taught various marketing classes at Purdue Univeristy Krannert School of Management and have worked in several companies, Korea Telecom, Samsung Electronics, and dunnhumby, as a marketing analyst. At Korea Telecom, his main roles as an entry level marketing researcher were to forecast sales and traffic of communication services and analyze data for CRM or more than 20 million consumers. After his first job, Jay Lee decided to expand his knowledge in marketing by joining the Ph.D. program at Purdue University Krannert School of Management. Once graduating he joined Samsung Electronics as a senior marketing manager. During Samsung, he conducted marketing intelligence and forecasted sales for mobile markets such as smartphones and tablets. Furthermore, monitored consumer analytics of these mobile products. Following the role at Samsung, he joined dunnhumby as a senior data solution analyst. At dunnhumby, he analyzed consumer transaction data for retailer industry, implemented schemes for consumer retention and loyalty programs, and provided client solutions for big data analyses.

Session Schedule

Earlybird ends on 12/10
January Session

Jan 9 - Feb 6, 2021 Saturday
  • 1January 9, 2021
  • 2January 16, 2021
  • 3January 23, 2021
  • 4January 30, 2021
  • 5February 6, 2021
10:00am-5:00pm

$2190.00
$2190.00
$2080.50
Enroll Now
Earlybird ends on 01/28
February Session

Feb 27 - Mar 27, 2021 Saturday
  • 1February 27, 2021
  • 2March 6, 2021
  • 3March 13, 2021
  • 4March 20, 2021
  • 5March 27, 2021
10:00am-5:00pm

$2190.00
$2190.00
$2080.50
Enroll Now

Save More by Enrolling in a Bundle

Bootcamp Prep
Introductory Python
Introductory Python
Data Science with Python: Data Analysis and Visualization
Data Science with Python: Data Analysis and Visualization
Data Science with R: Data Analysis and Visualization
Data Science with R: Data Analysis and Visualization
$5370.00
Total: $5370.00$5000.00
Data Science with R
Data Science with R: Data Analysis and Visualization
Data Science with R: Data Analysis and Visualization
Data Science with R: Machine Learning
Data Science with R: Machine Learning
$5180.00
Total: $5180.00$4662.00